Measurement of the Bs0 Lifetime and Production Rate with Ds−ℓ+ Combinations in Z Decays
INST NATL PHYS NUCL & PHYS PARTICULES | Laboratoire de Physique des Particules (LAPP) | Institut de Fisica d'Altes Energies | Universidad Aut��noma de Barcelona(Universitat Aut��noma de Barcelona | Dipartimento di Fisica | Istituto Nazionale Di Fisica Nucleare | Institute of High-Energy Physics | European Laboratory for Particle Physics (CERN) | European Organization for Nuclear Research(CERN) | Laboratoire de Physique Corpusculaire | Universite Blaise Pascal(Universit�� Blaise Pascal) | Niels Bohr Institute | Nuclear Research Center Demokritos (NRCD) | Ecole Polytechnique(Ecole Polytechnique | Laboratoire de Physique Nucléaire et des Hautes Energies | Department of Physics | Supercomputer Computations Research Institute | Laboratori Nazionali dell'INFN (LNF-INFN) | Laboratori Nazionali di Frascati di INFN(Laboratori Nazionali di Frascati | Department of Physics and Astronomy | University of Glasgow(University of Glasgow) | Institut für Hochenergiephysik | Institut für Experimentalphysik | Institut für Physik | Centre de Physique des Particules | IN2P3 Institut National de Physique Nucleaire et de Physique des Particules(IN2P3-CNRS | Max-Planck-Institut für Physik | Max-Planck-Institut f��r Physik (Werner-Heisenberg-Institut)(Max-Planck-Institut f��r Physik) | Laboratoire de l'Accélérateur Linéaire | Dipartimento di Fisica dell'Università | Scuola Normale Superiore di Pisa(Scuola Normale Superiore) | Particle Physics Dept. | CEA | Institute for Particle Physics | Fachbereich Physik | Universit?t Siegen(Universit?t Siegen | Universit�� degli Studi di Trieste(University of Trieste | Experimental Elementary Particle Physics | University of Wisconsin Madison(University of Wisconsin-Madison)
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

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